saasCNV (version 0.3.4)

cnv.call: CNV Calling from Sequencing Data

Description

Assign SCNA state to each segment directly from joint segmentation or from the results after segments merging step.

Usage

cnv.call(data, sample.id, segs.stat, maxL = NULL, N = 1000,  pvalue.cutoff = 0.05, seed = NULL, do.manual.baseline=FALSE, log2mBAF.left=NULL, log2mBAF.right=NULL,  log2ratio.bottom=NULL, log2ratio.up=NULL)

Arguments

data

a data frame containing log2ratio and log2mBAF data generated by cnv.data.

sample.id

sample ID to be displayed.

segs.stat

a data frame containing segment locations and summary statistics resulting from joint.segmentation or merging.segments.

maxL

integer. The maximum length in terms of number of probes a bootstrapped segment may span. Default is NULL. If NULL, It will be automatically specified as 1/100 of the number of data points.

N

the number of replicates drawn by bootstrap.

pvalue.cutoff

a p-value cut-off for CNV calling.

seed

integer. Random seed can be set for reproducibility of results.

do.manual.baseline

logical. If baseline adjustment to be done manually. Default is FALSE.

log2mBAF.left, log2mBAF.right, log2ratio.bottom, log2ratio.up

left, right, bottom and up boundaries to be specified manually by a visual inspectio of 2-D diagnosis plot generated by diagnosis.cluster.plot. These parameters are active when do.manual.baseline=TRUE.

Value

A few more columns have been add to the data frame resulting from joint.segmentation or merging.segments, which summarize the baseline adjusted median log2ratio, log2mBAF, p-values and CNV state for each segment.

Details

The baseline adjustment step is incorporated implicitly in the function.

See Also

joint.segmentation, merging.segments, cnv.data

Examples

data(seq.data)
data(seq.segs.merge)

## Not run: 
# seq.cnv <- cnv.call(data=seq.data, sample.id="PT116", 
#                     segs.stat=seq.segs.merge, maxL=2000, N=1000,
#                     pvalue.cutoff=0.05)
# ## End(Not run)

## how the results look like
data(seq.cnv)
head(seq.cnv)